A spreadsheet-based visualized Mindtool for improving students’ learning performance in identifying relationships between numerical variables

Abstract

In this study, a spreadsheet-based visualized Mindtool was developed for improving students’ learning performance when finding relationships between numerical variables by engaging them in reasoning and decision-making activities. To evaluate the effectiveness of the proposed approach, an experiment was conducted on the “phenomena of climate on earth” unit of an elementary school geography course. The experimental results showed that the spreadsheet-based visualized Mindtool significantly benefited the students in terms of improving their learning achievement and promoting their learning attitudes and satisfaction. Moreover, the cognitive load of the students was significantly decreased, indicating the effectiveness of this approach in helping students comprehend, learn content and organize their knowledge. To further investigate the learning behaviors of high-achievement and low-achievement students in using the spreadsheet-based Mindtool, a learning pattern analysis was conducted by coding the students’ behaviors recorded on video.

Keywords:

• computer-assisted learning
• Mindtools
• spreadsheets
• graphical interface
• technology-enhanced learning

Disclosure statement

No potential conflict of interest was reported by the authors.

Funding

This study is supported in part by the National Science Council of the Republic of China under contract numbers NSC 101-2511-S-011-005-MY3 and NSC 102-2511-S-011-007-MY3.

Notes on contributors

Ms. Chiu-Lin Lai is a Ph.D. student at the Graduate Institute of Applied Science and Technology, National Taiwan University of Science and Technology, Taiwan. Her research interests include computer-assisted learning and digital game-based learning.

Dr Gwo-Jen Hwang is currently a Chair Professor at the Graduate Institute of Digital Learning and Education, National Taiwan University of Science and Technology, Taiwan. His research interests include mobile and ubiquitous learning, digital game-based learning, web-based learning, and artificial intelligence in education.